Use new cached_params function

Author: penelopeysm

Project.toml

@@ -68,7 +68,7 @@ LinearAlgebra = "1.6"
 LogDensityProblems = "2"
 MCMCChains = "6, 7"
 MacroTools = "0.5.6"
-MarginalLogDensities = "0.4.1"
+MarginalLogDensities = "0.4.3"
 Mooncake = "0.4.147"
 OrderedCollections = "1"
 Printf = "1.10"

ext/DynamicPPLMarginalLogDensitiesExt.jl

@@ -195,9 +195,10 @@ function DynamicPPL.VarInfo(
 )
     # Extract the original VarInfo. Its contents will in general be junk.
     original_vi = mld.logdensity.logdensity.varinfo
-    # `mld.u` will contain the modes for any marginalized parameters
-    full_params = mld.u
-    # We can then set the values for any non-marginalized parameters
+    # Extract the stored parameters, which includes the modes for any marginalized
+    # parameters
+    full_params = MarginalLogDensities.cached_params(mld)
+    # We can then (if needed) set the values for any non-marginalized parameters
     if unmarginalized_params !== nothing
         full_params[MarginalLogDensities.ijoint(mld)] = unmarginalized_params
     end